Grieco, Ludovico Alberico (2026) Multi-Hazard Risk and Robustness Assessment of Existing Bridges. [Tesi di dottorato]

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Abstract

Many road bridges currently in service were designed decades ago, under standards that did not anticipate modern traffic demands, durability requirements, or exposure to multiple hazards. In Italy, most bridges were built between the 1950 and 1980 and now exhibit ageing materials, deterioration, and limited maintenance. Combined with the increasing frequency of natural and anthropic hazards, these factors have reduced structural reliability and raised concerns about network safety. Effective management therefore requires quantitative prioritisation strategies capable of supporting informed decisions and efficient allocation of limited resources. This thesis proposes a multi-hazard, multi-level methodology for risk assessment and prioritisation of existing bridges. At the territorial scale, a quantitative screening framework evaluates exposure to traffic, seismic, hydraulic, landslide, fire, vehicle impact, and blast hazards. Single-hazard risk indicators are computed and combined into multi-hazard risk indices through statistical Design of Experiment procedures and Monte Carlo simulations, explicitly accounting for uncertainty. The resulting indices allow bridges to be classified into different priority levels to support planning of inspections and timely intervention. At the site-specific scale, refined structural analyses are carried out on bridges identified as critical. A three-dimensional Applied Element Method model is used to investigate the collapse behaviour of a representative Gerber girder bridge deck under current traffic loading, different cross-girder configurations, and deterioration caused by reinforcement corrosion. Guidance is also provided for destructive testing plans to achieve appropriate knowledge levels, together with the calibration of partial safety factors for reinforced and prestressed concrete components at different structural scales. The methodology improves bridge management by linking network-level prioritisation with detailed assessment, enabling uncertainty-aware decisions and supporting safer, more sustainable infrastructure.

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